Use of an Empirical Model to Estimate Leaf Wetness Duration for Operation of a Disease Warning System Under a Shade in a Ginseng Field.

Ginseng foliar diseases are typically controlled by spray application using periodic schedules. Few disease warning systems have been used for effective control of ginseng foliar diseases because ginseng is grown under shade nettings, which makes it difficult to obtain weather data for operation of the disease warning system. Using weather data measured outside the shade as inputs to an empirical leaf wetness duration (LWD) model, LWD was estimated to examine if operation of a disease warning system would be feasible for control of ginseng foliar diseases. An empirical model based on a fuzzy logic system (fuzzy model) was used to estimate LWD at two commercial ginseng fields located in Gochang-gun and Jeongeup-si, Korea, in 2011 and 2012. Accuracy of LWD estimates was assessed in terms of mean error (ME) and mean absolute error (MAE). The fuzzy model tended to overestimate LWD during dew eligible days whereas it tended to underestimate LWD during rainfall eligible days. Still, daily disease risk ratings of the TOM-CAST disease warning system, which are derived from estimates of wetness duration and temperature, had a tendency to coincide with that derived from measurements of weather variables. As a result, spray advisory dates for the TOM-CAST disease warning system were predicted within ±3 days for about 78% of time windows during which the action threshold for spray application was reached. This result suggested that estimates of LWD using an empirical model would be helpful in control of a foliar disease in a ginseng field. It was also found that a spray application time model using meteorological observations may prove successful without the requirement of leaf wetness sensors within the field. Development of empirical correction schemes to the fuzzy model and a physical model for LWD estimation in a ginseng field could improve accuracy of LWD estimates and, as a result, spray advisory date prediction, which merits further studies.

Identification of quantitative trait loci for cadmium accumulation and distribution in rice (Oryza sativa).

Cadmium (Cd) poses a serious risk to human health due to its biological concentration through the food chain. To date, information on genetic and molecular mechanisms of Cd accumulation and distribution in rice remains to be elucidated. We developed an independent F7 RIL population derived from a cross between two japonica cultivars with contrasting Cd levels, 'Suwon490' and 'SNU-SG1', for QTLs identification of Cd accumulation and distribution. 'Suwon490' accumulated five times higher Cd in grain than 'SNU-SG1'. Large genotypic variations in Cd accumulation (17-fold) and concentration (12-fold) in grain were found among RILs. Significant positive correlations between Cd accumulation in grain with shoot Cd accumulation and shoot to grain distribution ratio of Cd signify that both shoot Cd accumulation and shoot to grain Cd distribution regulate Cd accumulation in japonica rice grain. A total of five main effect QTLs (scc10 for shoot Cd accumulation; gcc3, gcc9, gcc11 for grain Cd accumulation; and sgr5 for shoot to grain distribution ratio) were detected in chromosomes 10, 3, 9, 11, and 5, respectively. Of these, the novel potential QTL sgr5 has the strongest effect on shoot to grain Cd distribution. In addition, two digenic epistatic interaction QTLs were identified, suggesting the substantial contribution of nonallelic genes in genetic control of these Cd-related traits.

Population-specific quantitative trait loci mapping for functional stay-green trait in rice (Oryza sativa L.).

The functional stay-green trait gives leaves a longer duration of greenness and photosynthetic capacity during the grain-filling period. We developed two independent recombinant inbred line populations from the intra- and intersubspecific crosses of Oryza sativa L. subsp. japonica 'Suweon490' (japonica) × O. sativa subsp. japonica 'SNU-SG1' (japonica) and O. sativa subsp. indica 'Andabyeo' (indica) × O. sativa subsp. japonica 'SNU-SG1' (japonica), respectively. The common parental line 'SNU-SG1' was the functional source for the stay-green trait. Quantitative trait locus (QTL) mapping based on simple sequence repeat markers identified a total of six QTLs associated with two stay-green traits across two populations. The two traits were cumulative chlorophyll content (SPAD value) of flag leaf (CSFL) and total cumulative SPAD value of the four upper leaves (TCS). Four QTLs, tcs4, csfl6, csfl9 (or tcs9), and csfl12, located on chromosomes 4, 6, 9, and 12, respectively, were detected simultaneously in both populations. The remaining two QTLs, csfl2 (or tcs2) and tcs5, on chromosomes 2 and 5, respectively, were found to be population specific. Moreover, the functional stay-green trait of 'SNU-SG1' positively correlated with grain yield performance. Two yield QTLs, yld6 and yld9, on chromosomes 6 and 9 found in both populations were positioned at the same locations with the csfl6 and tcs9 QTLs for stay-green traits. Thus, the identified chromosomal regions can be promising targets of marker-assisted introgression of the functional stay-green trait into breeding materials for improvement of rice yield.

Modeling the Effects of Elevated Temperature and Weed Interference on Rice Grain Yield.

A 3-year phytotron study was conducted in Suwon (37.27°N, 126.99°E), Korea, to evaluate and model the effects of elevated temperature on rice-weed competition. The dry weight and the number of panicles in rice were the most susceptible components to weed interference during the early growth of rice, regardless of weed species, while other yield components, including the number of grains, % ripened grain, and 1000-grain weight, were more susceptible to elevated temperature. A rectangular hyperbolic model well demonstrated that rice grain yield was affected by weed interference under elevated temperature, showing that the competitiveness of late watergrass (Echinochloa oryzicola) and water chestnut (Eleocharis kuroguwai) increased under elevated temperature conditions. Quadratic and linear models well described the effects of elevated temperature on the weed-free rice grain yield and weed competitiveness values of the rectangular hyperbolic model for the two weed species, respectively. Thus, a combined rectangular hyperbolic model incorporated with the quadratic and linear models well demonstrated the effects of elevated temperature and weed interference on rice grain yield across years. Using the combined model and estimated parameters, the rice grain yields were estimated to be 58.9, 48.5, 41.3, and 35.9% of the yields under weed-free conditions for 80 plants m-2 of late watergrass and 86.8, 64.3, 51.1, and 42.3% of the yields under weed-free conditions for 80 plants m-2 of water chestnut at 1,300, 1,500, 1,700, and 1,900°C·days of accumulated growing degree days (GDD; from transplanting to flowering, 89 days), respectively. The combined model developed in this study can provide an empirical description of both the elevated temperature and weed interference effects on rice yield and can be used for predicting rice grain yields due to weed interference under future elevated temperature conditions.

Earlier planting offsets the adverse effect of global warming on spring potato in South Korea.

Potato is one of the most important food crops in South Korea, but the climate change impact on potato production is not clearly understood due to the complex topography across the nation. The climate change impact on spring potato was assessed with a fine-resolution (1-km) simulation using the SUBSTOR-potato model and five regional climate models based on the Representative Concentration Pathways 8.5. Compared to the current climate, the future climates were projected to be more favorable for the spring potato production, which contrasts the previous simulation studies using general circulation models with coarse resolutions (0.5-1.0°). Without any adaptations, anticipated warming was projected to decrease potato yield by -7.7% in the 2080s. However, growing season length (GSL) could be extended by 18.5 days with earlier planting, which eventually over-compensated the negative warming effect. With consideration of the CO2 fertilization effect, overall climate change impact could be up to +80% in the 2080s. In addition, replacing the current early cultivar "Superior" with mid-late cultivars will provide additional yield gain in the coastal areas. Meanwhile, in the inland areas, breeding of frost- and heat-tolerance cultivars will be required for additional yield gain. Still, cautious interpretation is needed since the CO2 fertilization effect might be over-estimated and that the farmers may not extend GSL as much as in the current study from the economic point of view (i.e., farmers may harvest earlier when the market price of potato is high). This study highlights that a fine spatial resolution is essential for the realistic simulation of the climate change impact in complex terrain.

A surrogate weighted mean ensemble method to reduce the uncertainty at a regional scale for the calculation of potential evapotranspiration.

We propose a weighted ensemble approach using a surrogate variable. As a case study, the degree of agreement (DOA) statistics for potential evapotranspiration (PET) was determined to compare the ordinary arithmetic mean ensemble (OAME) method and the surrogate weighted mean ensemble (SWME) method for three domains. Solar radiation was used as the surrogate variable to determine the weight values for the ensemble members. Singular vector decomposition with truncation values was used to select five ensemble members for the SWME method. The SWME method tended to have greater DOA statistics for PET than the OAME method with all available models. The distribution of PET values for the SWME method also had greater DOA statistics than that for the OAME method over relatively large spatial extent by month. These results suggest that the SWME method based on the weight value derived from the surrogate variable is suitable for exploiting both diversity and elitism to minimize the uncertainty of PET ensemble data. These findings could contribute to a better design of climate change adaptation options by improving confidence of PET projection data for the assessment of climate change impact on natural and agricultural ecosystems using the SWME method.

Differential Mechanisms of Potato Yield Loss Induced by High Day and Night Temperatures During Tuber Initiation and Bulking: Photosynthesis and Tuber Growth.

The tuber yield of potatoes is vulnerable to high temperature and is challenged by the asymmetric increase in day and night temperatures. This study aimed to evaluate photosynthesis, biomass growth, tuber mass distribution, and dry tuber yield in early harvested potatoes that were field-grown under high day and night temperature conditions during different growth stages. Potatoes were exposed to ambient (control), high night temperature (HNT; 19:00-7:00), high day temperature (HDT; 7:00-19:00), and high day/night temperature (HDNT; all day) for 14 days during tuber initiation (TI) or tuber bulking (TB) using portable, temperature-controlled plastic houses that were controlled to increase the temperature by 4.0°C. During TI, HNT delayed tuber development, thus altering tuber mass distribution by reducing the yield proportion of large tubers of >100 g (-53.7%) and lowering early harvest index (-16.1%), causing a significant yield loss (-17.2%) without interfering with photosynthesis. In contrast, HDT decreased early tuber yield (-18.1%) by reducing photosynthetic sources, which was probably attributed to decreased photosynthetic efficiency through a feedback inhibition. However, HDT altered neither tuber mass distribution nor early harvest index. HDNT during TI exhibited all the aforementioned effects of HNT and HDT (i.e., cumulative effects): reduced yield proportion of large tubers (-46.7%), decreased early harvest index (-23.7%), and reduced photosynthetic rate; thus, HDNT caused the highest yield loss (-30.3%). During TB, when the tubers were fully developed, the thermal effects decreased because most of the effects were either directly or indirectly linked to tuber development. These results provide comprehensive insight to the differential mechanisms of potato yield loss under high day and night temperatures and show that further field experiments should be conducted to cope with the threat of global warming on potato production.

Assimilating MODIS data-derived minimum input data set and water stress factors into CERES-Maize model improves regional corn yield predictions.

Crop growth models and remote sensing are useful tools for predicting crop growth and yield, but each tool has inherent drawbacks when predicting crop growth and yield at a regional scale. To improve the accuracy and precision of regional corn yield predictions, a simple approach for assimilating Moderate Resolution Imaging Spectroradiometer (MODIS) products into a crop growth model was developed, and regional yield prediction performance was evaluated in a major corn-producing state, Illinois, USA. Corn growth and yield were simulated for each grid using the Crop Environment Resource Synthesis (CERES)-Maize model with minimum inputs comprising planting date, fertilizer amount, genetic coefficients, soil, and weather data. Planting date was estimated using a phenology model with a leaf area duration (LAD)-logistic function that describes the seasonal evolution of MODIS-derived leaf area index (LAI). Genetic coefficients of the corn cultivar were determined to be the genetic coefficients of the maturity group [included in Decision Support System for Agrotechnology Transfer (DSSAT) 4.6], which shows the minimum difference between the maximum LAI derived from the LAD-logistic function and that simulated by the CERES-Maize model. In addition, the daily water stress factors were estimated from the ratio between daily leaf area/weight growth rates estimated from the LAD-logistic function and that simulated by the CERES-Maize model under the rain-fed and auto-irrigation conditions. The additional assimilation of MODIS data-derived water stress factors and LAI under the auto-irrigation condition showed the highest prediction accuracy and precision for the yearly corn yield prediction (R2 is 0.78 and the root mean square error is 0.75 t ha-1). The present strategy for assimilating MODIS data into a crop growth model using minimum inputs was successful for predicting regional yields, and it should be examined for spatial portability to diverse agro-climatic and agro-technology regions.

Quantitative trait loci associated with functional stay-green SNU-SG1 in rice.

During monocarpic senescence in higher plants, functional stay-green delays leaf yellowing, maintaining photosynthetic competence, whereas nonfunctional stay-green retains leaf greenness without sustaining photosynthetic activity. Thus, functional stay-green is considered a beneficial trait that can increase grain yield in cereal crops. A stay-green japonica rice 'SNU-SG1' had a good seed-setting rate and grain yield, indicating the presence of a functional stay-green genotype. SNU-SG1 was crossed with two regular cultivars to determine the inheritance mode and identify major QTLs conferring stay-green in SNU-SG1. For QTL analysis, linkage maps with 100 and 116 DNA marker loci were constructed using selective genotyping with F2 and RIL (recombinant inbred line) populations, respectively. Molecular marker-based QTL analyses with both populations revealed that the functional stay-green phenotype of SNU-SG1 is regulated by several major QTLs accounting for a large portion of the genetic variation. Three main-effect QTLs located on chromosomes 7 and 9 were detected in both populations and a number of epistatic-effect QTLs were also found. The amount of variation explained by several digenic interactions was larger than that explained by main-effect QTLs. Two main-effect QTLs on chromosome 9 can be considered the target loci that most influence the functional stay-green in SNU-SG1. The functional stay-green QTLs may help develop low-input high-yielding rice cultivars by QTL-marker-assisted breeding with SNU-SG1.

Phenology and Seed Yield Performance of Determinate Soybean Cultivars Grown at Elevated Temperatures in a Temperate Region.

Increased temperature means and fluctuations associated with climate change are predicted to exert profound effects on the seed yield of soybean. We conducted an experiment to evaluate the impacts of global warming on the phenology and yield of two determinate soybean cultivars in a temperate region (37.27°N, 126.99°E; Suwon, South Korea). These two soybean cultivars, Sinpaldalkong [maturity group (MG) IV] and Daewonkong (MG VI), were cultured on various sowing dates within a four-year period, under no water-stress conditions. Soybeans were kept in greenhouses controlled at the current ambient temperature (AT), AT+1.5°C, AT+3.0°C, and AT+5.0°C throughout the growth periods. Growth periods (VE-R7) were significantly prolonged by the elevated temperatures, especially the R1-R5 period. Cultivars exhibited no significant differences in seed yield at the AT+1.5°C and AT+3.0°C treatments, compared to AT, while a significant yield reduction was observed at the AT+5.0°C treatment. Yield reductions resulted from limited seed number, which was due to an overall low numbers of pods and seeds per pod. Heat stress conditions induced a decrease in pod number to a greater degree than in seed number per pod. Individual seed weight exhibited no significant variation among temperature elevation treatments; thus, seed weight likely had negligible impacts on overall seed yield. A boundary line analysis (using quantile regression) estimated optimum temperatures for seed number at 26.4 to 26.8°C (VE-R5) for both cultivars; the optimum temperatures (R5-R7) for single seed weight were estimated at 25.2°C for the Sinpaldalkong smaller-seeded cultivar, and at 22.3°C for the Daewonkong larger-seeded cultivar. The optimum growing season (VE-R7) temperatures for seed yield, which were estimated by combining the two boundary lines for seed number and seed weight, were 26.4 and 25.0°C for the Sinpaldalkong and Daewonkong cultivars, respectively. Considering the current soybean growing season temperature, which ranges from 21.7 (in the north) to 24.6°C (in the south) in South Korea, and the temperature response of potential soybean yields, further warming of less than approximately 1°C would not become a critical limiting factor for soybean production in South Korea.

Assessment of microclimate conditions under artificial shades in a ginseng field.

BACKGROUND: Knowledge on microclimate conditions under artificial shades in a ginseng field would facilitate climate-aware management of ginseng production. METHODS: Weather data were measured under the shade and outside the shade at two fields located in Gochang-gun and Jeongeup-si, Korea, in 2011 and 2012 seasons to assess temperature and humidity conditions under the shade. An empirical approach was developed and validated for the estimation of leaf wetness duration (LWD) using weather measurements outside the shade as inputs to the model. RESULTS: Air temperature and relative humidity were similar between under the shade and outside the shade. For example, temperature conditions favorable for ginseng growth, e.g., between 8°C and 27°C, occurred slightly less frequently in hours during night times under the shade (91%) than outside (92%). Humidity conditions favorable for development of a foliar disease, e.g., relative humidity > 70%, occurred slightly more frequently under the shade (84%) than outside (82%). Effectiveness of correction schemes to an empirical LWD model differed by rainfall conditions for the estimation of LWD under the shade using weather measurements outside the shade as inputs to the model. During dew eligible days, a correction scheme to an empirical LWD model was slightly effective (10%) in reducing estimation errors under the shade. However, another correction approach during rainfall eligible days reduced errors of LWD estimation by 17%. CONCLUSION: Weather measurements outside the shade and LWD estimates derived from these measurements would be useful as inputs for decision support systems to predict ginseng growth and disease development.

Computational identification of anthocyanin-specific transcription factors using a rice microarray and maximum boundary range algorithm.

This study identifies 2,617 candidate genes related to anthocyanin biosynthesis in rice using microarray analysis and a newly developed maximum boundary range algorithm. Three seed developmental stages were examined in white cultivar and two black Dissociation insertion mutants. The resultant 235 transcription factor genes found to be associated with anthocyanin were classified into nine groups. It is compared the 235 genes by transcription factor analysis and 593 genes from among clusters of COGs related to anthocyanin functions. Total 32 genes were found to be expressed commonly. Among these, 9 unknown and hypothetical genes were revealed to be expressed at each developmental stage and were verified by RT-PCR. These genes most likely play regulatory roles in either anthocyanin production or metabolism during flavonoid biosynthesis. While these genes require further validation, our results underline the potential usefulness of the newly developed algorithm.

Differentially expressed genes related to symbiotic association in a supernodulating soybean mutant and its wild-type.

SUMMARY To understand the molecular basis of symbiotic association, a cDNA-AFLP technique was used to identify differentially expressed transcripts between a supernodulating soybean mutant, SS2-2, and its wild-type, Sinpaldalkong 2. As sources of cDNA-AFLP templates, trifoliates of 2-week-old plants were collected 1 week after Bradyrhizobium japonicum inoculation. A total of 147 bands out of 4000 amplicons were recognized as differentially expressed fragments, with 40 transcript-derived fragments (TDFs) in SS2-2 and 65 TDFs in Sinpaldalkong 2. Qualitative and quantitative real-time RT-PCR assays suggested that the expression patterns of genes in both genotypes were clearly differentiated. TDFs homologous to nodulin (65S2) and a putative senescence-associated protein (9S1) were up-regulated in SS2-2, whereas Sinpaldalkong 2 showed up-regulation of a receptor-like kinase (48sin1) and a kinase-like protein (17sin1). This indicates that different genes may be involved in regulation of the symbiotic programme that distinguishes SS2-2 from its wild-type. A TDF showing a change in a single base from A (Sinpaldalkong 2) to T (SS2-2) in this study was identified as a Glycine max nodule autoregulation receptor-like protein kinase precursor, previously identified by map-based cloning. These results demonstrate that cDNA-AFLP is a powerful technique to detect interesting genes without prior assumptions about the nature of the genes. The differentially expressed genes between Sinpaldalkong 2 and SS2-2 suggest that different signal transduction pathways for symbiosis may be involved in the two soybean genotypes.

Newly featured infection events in a supernodulating soybean mutant SS2-2 by Bradyrhizobium japonicum.

Supernodulating soybean (Glycine max L. Merr.) mutant SS2-2 and its wild-type counterpart, Sinpaldalkong 2, were examined for the microstructural events associated with nodule formation and development. SS2-2 produced a substantially higher percentage of curled root hairs than the wild type, especially at 14 days after inoculation with Bradyrhizobium japonicum. In addition, there was new evidence that in SS2-2, B. japonicum also entered through fissures created by the emerging adventitious root primordia. Early steps of nodule ontogeny were faster in SS2-2, and continued development of initiated nodules was more frequent and occurred at a higher frequency than in the wild type. These data suggest that the early expression of autoregulation is facilitated by decreasing the speed of cortical cell development, leading to the subsequent termination of less-developed nodules. The nodules of SS2-2 developed into spherical nodules like those formed on the wild type. In both the wild type and supernodulating mutant, vascular bundles bifurcate from root stele and branch off in the nodule cortex to surround the central infected zone. These findings indicate that SS2-2 has complete endosymbiosis and forms completely developed nodule vascular bundles like the wild type, but that the speed of nodule ontogeny differs between the wild type and SS2-2. Thus, SS2-2 has a novel symbiotic phenotype with regard to nodule organogenesis.